You have a 2D NumPy array representing exam scores. How can you use np.where() to create a new array where scores below 50 are replaced with 'Fail' and others with 'Pass'?

hard📝 Application Q8 of 15

NumPy - Indexing and Slicing

You have a 2D NumPy array representing exam scores. How can you use np.where() to create a new array where scores below 50 are replaced with 'Fail' and others with 'Pass'?

Anp.where(scores >= 50, 'Fail', 'Pass')

Bnp.where(scores < 50, 'Fail', 'Pass')

Cnp.where(scores == 50, 'Fail', 'Pass')

Dnp.where(scores < 50, scores, 'Pass')

Step-by-Step Solution

Solution:

Step 1: Define condition for failing scores
Scores below 50 are failing, so condition is scores < 50.
Step 2: Use np.where to assign 'Fail' or 'Pass'
Use np.where(scores < 50, 'Fail', 'Pass') to create new array with labels.
Final Answer:
np.where(scores < 50, 'Fail', 'Pass') -> Option B
Quick Check:
np.where(condition, 'Fail', 'Pass') labels scores [OK]

Quick Trick: Use condition for Fail, else Pass in np.where [OK]

Common Mistakes:

Reversing condition
Using equality instead of less than
Mixing numeric and string outputs incorrectly

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More NumPy Quizzes

You have a 2D NumPy array representing exam scores. How can you use np.where() to create a new array where scores below 50 are replaced with 'Fail' and others with 'Pass'?

Step 1: Define condition for failing scores

Step 2: Use np.where to assign 'Fail' or 'Pass'

Final Answer:

Quick Check:

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